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Example 35
Constraining the Parameters
In this example, variances and covariances will be required to be invariant across
groups. This is the assumption of homogeneity of variances and covariances that is
often made in discriminant analysis and some kinds of clustering. In principle, the
assumption of homogeneity of variances and covariances is not necessary in mixture
modeling. The reason we will make the assumption here is that, for this example, the
algorithm in Amos fails without that assumption. (It should be noted that the scatterplot
in Example 34 suggests that the assumption is violated.)